In the field of neuroscience today there are a number of cognitive testing paradigms used by physicians, clinicians and individuals to assess one's cognitive performance.
The first and the most commonly used cognitive testing paradigm, especially the one that traces its origins furthest back in time, is the survey. The survey is a multipart questionnaire that is typically administered by a physician or a clinician. The set of questions in a survey, which may comprise of qualitative or quantitative questions, ask the individual taking the survey to evaluate oneself. Once the individual is finished taking the survey, the clinician or physician then evaluates the answers to the questions. The answers are evaluated in one of two ways. The answers are either subjectively evaluated by the physician or clinician, or entered into an algorithm to be processed to generate a score. The evaluation is then used to determine whether the cognitive level of performance of an individual meets a certain threshold or not to determine cognitive impairment.
The advantages to the survey are that it is portable and fairly easy to administer. In addition, the survey cognitive testing paradigm allows the test designer a great degree of freedom and flexibility in what questions to ask and the format of the test taker to answer those questions. However, there are downsides to surveys. One downside is that surveys are unfortunately relatively qualitative. Also, surveys are often open survey forms, where multiple choice and open-ended questions alike tend to convert into subjective answers. For instance, a test that asks, “How dizzy are you? Please quantify on a scale of one to ten” is not a truly quantitative test, but rather a subjective measurement of experience of the patient filling out the survey. A similar type of measurement error occurs if the question was asked in a multiple-choice format with answer choices of yes and no. Here, the patient then must select yes if they feel something, or select no if they don't feel dizzy or don't know what they might be assessing to feel. The survey paradigm also suffers when it relates to cognitive function because it presupposes a uniformly defined normative universally appreciated and semantically similar way of describing ailments from patient to patient.
Another common type of cognitive assessment is to study the reaction time of a patient in response to a test. Reaction time is typically used with recordings, and stopwatches or clocks. In recent time, reaction time tests area administered via tests on computers or over the Internet using keyboards or mice as input methods. Such reaction tests are conducted by presenting questions on the screen that the patient reacts to by pressing the input device. The data is then collected in the form of milliseconds of response time that the patient had to think and compute. This data is then aggregated and typically processed by methods such as average and standard deviation over the course of multiple trials in order to get a midline value or range of reaction time for a certain type of test.
Reaction time tests also attempt to analyze decision making by presenting a question that the patient must respond to make very quickly by pressing one or multiple types of stimuli. An example of such a reaction time test would be the following: the test involves the display of two different icons and the patient is asked to press the space bar only if one icon appears but not when the other icon appears. The result of this is that the reaction time test also measures the quality of the reaction with the decision, and not just the reaction time in general.
Unfortunately, reaction time tests have many disadvantages. Reaction time tests, while somewhat quantitative, suffer from low “test re-test reliability” and high degree of error induced by the environmental control. There are simply too many other variables at play. Also, the process of measuring reaction time needs to be iterated many times, often in the hundreds or thousands range, in order to produce a meaningful figure. The biggest problem with these tests however is that these tests are highly reliant on the patient's willingness or will to take the test. The resulting outcome then is more oftentimes a function of patient willingness to take a test and not the patient exhibiting the symptom or the phenomena that one is looking to measure in the first place.
A more modern cognitive testing paradigm is the balance test. The balance test paradigm may ask a patient to sit or stand on a ball, such as a balance ball, in some off-center form. With the use of cameras or measuring devices such as semiconductor components being placed on the patient, the system measures how stable the patient is to determine the cognitive ability associated with the brain circuit pathway for balancing.
The downfalls of balance tests are that balance based tests are quite noisy. The noise is because of several variables being at play in the process of measuring them, and the devices used to measure the variables, such as cameras, accelerometers and other forms of driverscalpic sensing, are simply not advanced enough to produce a reliable metric. Furthermore, the measurement of balance tends to be fairly binary, i.e. stable or unstable. Moreover, connecting the instability measurements to specific types of cognitive decline is quite difficult because disorientation can be caused by effects unrelated to cognitive ability such as a headache, a blockage in the ear canal and dizziness.
Neuroimaging technologies have also been used to assess cognitive performance. Neuroimaging technologies are generally broken into two different categories of testing. The first category of neuroimaging technologies includes those that analyze images, such as fMRI and CT scans. The second category of neuroimaging technologies includes those that analyze waveforms, which typically are EEG or MEG technologies.
The neuroimaging technologies that use imaging rely on an imaging system, which captures some form of metabolic or electric activity inside the brain. This activity is typically mapped in a topological way to the three-dimensional coordinates of the brain. There is typically a one to one mapping between the section of the brain with activity and the physical location of the brain. Typically slices, map or pictures of the brain are taken at various locations inside the brain, but the mechanism underlying those imaging technologies is capturing the metabolic rate of the neurons as they are activated by the brain in order to process signals. Metabolism typically takes the form of a consumption of glucose or sugars or some form of chemical in the brain that generates some kind of activity, such as a waveform of heat or electrical activity. This is a coarse grain way of assessing what part of the brain in general is consuming energy at any given time.
The second type of imaging relies on the analysis of the movement of liquid or fluid or the emission of electrical or magnetic signals in the brain. The waveform based cognitive neuroimaging technologies rely on surface based analysis, based on sensors that are placed on the skull on the outside of the head which read electrical or magnetic activity. As the sensors are positioned on the outside surface of the head, the depth in which they can measure activity in the brain is limited. Thus the sensors generally have a more difficult time measuring waveforms or activities inside the brain closer to the brain stem. However, as a very high level measure, the sensors can also generate an assessment of where the user's brain is active at any given time.
Neuroimaging technologies suffer a variety of problems, although to date they have been perhaps the most promising and eye opening about the relationship between the physical location of impairment with behavioral impairment or change. One of the problems is the problem of not knowing what variables to compare during the testing process. For example, it is unclear if the images should be compared from one patient to another patient, a patient to a population statistical average, or a patient to their baseline taken at some previous time. However, whether it is from patient to patient, from patient to a population statistical average, or from patient to himself or herself, there are too many variables to consider and cannot make anything more than generalizations about the conclusions of the patient's cognitive performance. Furthermore, both neuroimaging and their related signal analysis in the cognitive assessment paradigms suffer from the challenge of having noisy data. The high level of noise usually drowns out the signal that one would wish to analyze. On top of the noise from the devices and the surrounding environment, the background of mental activity is often difficult to filter out of the actual signal associated with the one being tested for and prevents doing any kind of meaningful analysis.
Another paradigm of promising cognitive assessment is by biomarkers, diagnostic tests or bioassays. This form of cognitive assessment generally relies on the breakdown of particles inside the brain via some kind of emission of particles from the cell from the neuron into the blood stream. As damaged cells emit byproducts of neuron structures into the blood stream, measuring the presence or availability of those breakdown byproducts can be used to determine if any cognitive damage has occurred in the brain and the severity of the damage. The challenge of these tests in general is that they tend to be invasive or require bodily fluid sampling. In addition, it is very difficult to correlate the results of the test with the precise location of the damage with just fluid sampling alone, such as blood or urine sampling. Therefore, at best this paradigm serves as a high level indicator of brain damage, but not the location of the damage.
The most promising of these neuro-diagnostic tests and cognitive evaluation test platforms is perhaps eye tracking. Eye tracking is used to look at the movements of the eyes in a response to a series of tests or stimuli that the patient must either follow or void or count or tally with their eyes. By measuring the fluidity, momentum and precision of the movement of the eyes as they track objects that are likewise moving or reacting on the screen, a more precise level of various cognitive functions can be determined. The distinction here is that the cognitive function is evaluated as opposed to the physical structure of the brain. This is promising because as one is measuring the physical structure of the brain, the measurement has very little correlation to the actual cognitive function.
Across all of these cognitive testing paradigms, there is a general set of problems such as the long length of time to administer the test, the time taken by the test taker and the test itself from start to finish, and the requirement of trained personnel and experts. Also, the cost of running these tests is very high, not to mention the cost for the administrator to not just run the test, but to be educated about the test.
It is important to note that various cognitive testing paradigms have been employed in the past in an attempt to be used in the process of drug development. However, these paradigms have suffered a number of drawbacks over the subject matter.